R package forecast v7.2 now on CRAN

[This article was first published on R on Rob J Hyndman, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

I’ve pushed a minor update to the forecast package to CRAN. Some highlights are listed here.
Plotting time series with ggplot2 You can now facet a time series plot like this:
library(forecast) library(ggplot2) lungDeaths <- cbind(mdeaths, fdeaths) autoplot(lungDeaths, facets=TRUE) So autoplot.mts now behaves similarly to plot.mts Multi-step fitted values The fitted function has a new argument h to allow computation of in-sample fitted values of more than one-step-ahead. In time series, fitted values are defined as the one-step-forecasts of the data used in training a model.

To leave a comment for the author, please follow the link and comment on their blog: R on Rob J Hyndman.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)